Future wireless networks will be composed of multiple radio access technologies (RATs). To benefit from these, users must utilize the appropriate RAT, and access points (APs). In this thesis we evaluate the efficiency of selection criteria that, in addition to path-loss and system bandwidth, also consider load. The problem is studied for closed as well as open systems. In the former both terminals and infrastructure are controlled by a single actor (e.g., mobile operator), while the latter refers to situations where terminals, selfishly, decide which AP it wants to use (as in a common market-place). We divide the overall problem into the prioritization between available RATs and, within a RAT, between the APs. The results from our studies suggest that data users, in general, should be served by the RAT offering highest peak data rate.As this can be estimated by terminals, the benefits from centralized RAT selection is limited. Within a subsystem, however, load-sensitive AP selection criteria can increase data-rates. Highest gains are obtained when the subsystem is noise-limited, deployment unplanned, and the relative difference in number of users per AP significant. Under these circumstances the maximum supported load can be increased by an order of magnitude. However, also decentralized AP selection, where greedy autonomous terminal-based agents are in charge of the selection, were shown to give these gains as long they accounted for load. We also developed a game-theoretic framework, where users competed for wireless resources by bidding in a proportionally fair divisible auction. The framework was applied to a scenario where revenue-seeking APs competed for traffic by selecting an appropriate price. Compared to when APs cooperated, modelled by the Nash bargaining solution, our results suggest that a competitive access market, where infrastructure is shared implicitly, generally, offers users better service at a lower cost. Although AP revenues reduce, this reduction is, relatively, small and were shown to decrease with the concavity of demand. Lastly we studied whether data services could be offered in a discontinuous high-capacity network by letting a terminal-based agent pre-fetch information that its user potentially may request at some future time-instant. This decouples the period where the information is transferred, from the time-instant when it is consumed. Our results show that above some critical AP density, considerably lower than that required for continuous coverage, services start to perform well.